Inertial measurement devices, such as gyroscopes and accelerometers, provide high-precision sensing, however, historically, their cost, size, and power requirements have prevented their widespread use in industries such as consumer products, gaming devices, automobiles, and handheld positioning systems. More recently, micro-electro-mechanical systems (MEMS) device implementations of gyroscopes and accelerometers have been gaining increased attention from multiple industries since micro-machining technologies have made fabrication of miniature gyroscopes and accelerometers possible. Miniaturization also enables integration of multiple MEMS devices with readout electronics on the same die, resulting in reduced size, cost, and power consumption as well as improved resolution by reducing noise.
Current integrated circuit component implementations of a MEMS system containing multiple inertial measurement devices use separate analog signal processing blocks for each unique MEMS device, such signal processing blocks, typically include a trans-impedance amplifier (TIA), programmable gain amplifier (PGA), zero-IF mixer (ZIF Mixer), and a rate amplifier (Rate-Amp), collectively usually referred to as “sense channel”, for each MEMS device in the MEMS system. Such designs include multiple occurrences of identical components and add to the space, expense and fabrication complexity of the MEMS system.
Accordingly, a need exists for a more efficient signal processing architecture for a system having multiple MEMS devices which eliminates the redundancy of multiple occurrences of identical components.
Further, sensor outputs drift with changes in the external conditions such as temperature, stress, humidity, etc. These undesired effects cannot be corrected using a single factory calibration since environmental changes can be drastic during the normal operation of a device. As such, dynamic calibration of sensor signal errors is critical for sensors that are susceptible to environmental stresses that change over time.
Accordingly, a need exists for a multiplexed signal processor architecture to perform dynamic calibration of all sensor error signals such that the undesired effects are reduced to meet the application requirements.